ArticleAnnals of translational medicine2022
Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer's disease.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Upregulation of SLC38A2 by melatonin attenuates hippocampal ferroptosis in Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- APOE4-driven T cell dysregulation in Alzheimer's disease: single-cell genomics and Mendelian randomization reveal novel therapeutic targets.Journal of neuroinflammation · 2026Article
- Cross study transcriptomic investigation of Alzheimer's brain tissue discoveries and limitations.Scientific reports · 2025Article
- Network dynamics-based subtyping of Alzheimer's disease with microglial genetic risk factors.Alzheimer's research & therapy · 2024Article
- Profiling of long non-coding RNAs in hippocampal-entorhinal system subfields: impact of RN7SL1 on neuroimmune response modulation in Alzheimer's disease.Journal of neuroinflammation · 2024Article
- Competing endogenous RNAs in human astrocytes: crosstalk and interacting networks in response to lipotoxicity.Frontiers in neuroscience · 2023Article
- Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis.Frontiers in aging neuroscience · 2023Article
- JUN and PDGFRA as Crucial Candidate Genes for Childhood Autism Spectrum Disorder.Frontiers in neuroinformatics · 2022Article
- Integrated analysis and identification of hub genes as novel biomarkers for Alzheimer's disease.Frontiers in aging neuroscience · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Alzheimer's disease (AD) is closely related to immunity and competitive endogenous RNAs (ceRNAs) are believed to play a key role in the development of AD. Therefore, understanding the ceRNA network related to AD immunity will contribute to the identification of novel immunotherapeutic targets and provide new insights into AD from an immunological perspective. Methods: Weighted gene coexpression network analysis (WGCNA) and Enrichr enrichment analysis were performed to identify the immune-related gene coexpression modules through microarray datasets from the Gene Expression Omnibus (GEO) database. The differentially expressed long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) were identified from the microarray through differential analysis and mapped with related databases. Cytoscape was used to construct a lncRNA-miRNA-mRNA network. Subsequently, ImmuCellAI immune infiltration analysis was performed and a ceRNA sub-network of related core immune cells was constructed. Finally, the potential pathways related to these core factors were determined through gene set enrichment analysis (GSEA). Results: Through WGCNA analysis and enrichment analysis, the blue module and the green module were identified as key modules related to AD immunity. Naïve CD8 cells were shown to be the key immune cells related to AD. Correlation analysis and receiver operating characteristic (ROC) curves verified lncRNA Long Intergenic Non-Protein Coding RNA 472 (LINC00472), lncRNA HLA Complex Group 18 (HCG18), RUNX Family Transcription Factor 3 (RUNX3), Tensionin 1 (TNS1), Linker For Activation Of T Cells Family Member 2 (LAT2), and Solute Carrier Family 38 Member 2 (SLC38A2) as possible key targets related to AD immunity. Conclusions: The lncRNA LINC00472, lncRNA HCG18, RUNX3, TNS1, LAT2, and SLC38A2 identified in this study may be key targets related to AD immunity. These insights will provide future directions for the further AD research.
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